The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Pattern-oriented modelling: a ‘multi-scope’ for predictive systems ecology
Open accessAbstract
Modern ecology recognizes that modelling systems across scales and at multiple levels—especially to link population and ecosystem dynamics to individual adaptive behaviour—is essential for making the science predictive. ‘Pattern-oriented modelling’ (POM) is a strategy for doing just this. POM is the multi-criteria design, selection and calibration of models of complex systems. POM starts with identifying a set of patterns observed at multiple scales and levels that characterize a system with respect to the particular problem being modelled; a model from which the patterns emerge should contain the right mechanisms to address the problem. These patterns are then used to (i) determine what scales, entities, variables and processes the model needs, (ii) test and select submodels to represent key low-level processes such as adaptive behaviour, and (iii) find useful parameter values during calibration. Patterns are already often used in these ways, but a mini-review of applications of POM confirms that making the selection and use of patterns more explicit and rigorous can facilitate the development of models with the right level of complexity to understand ecological systems and predict their response to novel conditions.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Platt, J. R. (1964) · Science · doi:10.1126/science.146.3642.347 · Cited by 2,907
Research works printed but not linked: 49
- 10.1111/j.1469-185X.2009.00106.x · doi:10.1111/j.1469-185x.2009.00106.x
- 10.1007/s10021-008-9166-8 · DOI
- 10.1017/S0266467406003221 · doi:10.1017/s0266467406003221
- 10.1098/rstb.2009.0155 · DOI · Paper page
- 10.1016/0304-3800(94)90056-6 · DOI
- 10.1016/0048-9697(95)04966-5 · DOI · Paper page
- 10.1126/science.1116681 · DOI · Paper page
- Grimm V., 2004, Handbook of scaling methods in aquatic ecology: measurement, analysis, simulation, 411
- 10.1034/j.1600-0706.2003.12027.x · DOI · Paper page
- 10.1515/9781400850624 · DOI · Paper page
- 10.1016/j.tree.2008.02.005 · DOI · Paper page
- Railsback S. F., 2012, Agent-based and individual-based modeling: a practical introduction.
- von Bertalanffy L., 1968, General system theory: foundations, development, applications.
- 10.1016/j.jhydrol.2005.07.007 · DOI · Paper page
- 10.1023/b:bioc.0000004313.86836.ab · DOI
- 10.1016/j.ecolmodel.2010.08.019 · DOI · Paper page
- 10.1016/S0304-3800(00)00298-2 · DOI · Paper page
- 10.2307/5591 · DOI · Paper page
- 10.1016/S0034-4257(01)00255-3 · DOI
- 10.1111/j.1600-0706.2009.18284.x · DOI · Paper page
- 10.1111/j.1461-0248.2011.01640.x · DOI · Paper page
- 10.1890/0012-9615(2006)076[0601:DIGFWI]2.0.CO;2 · doi:10.1890/0012-9615(2006)076[0601:digfwi]2.0.co;2
- 10.1111/j.1365-2664.2008.01526.x · DOI · Paper page
- 10.1016/j.ecolmodel.2010.03.015 · DOI
- 10.1016/j.ecolmodel.2007.03.033 · doi:10.1016/j.ecolmodel.2007.03.033
- 10.1086/659623 · DOI
- 10.1038/nature06813 · DOI · Paper page
- 10.1016/j.ecolmodel.2007.02.008 · doi:10.1016/j.ecolmodel.2007.02.008
- 10.1890/06-1670.1 · doi:10.1890/06-1670.1
- 10.1016/j.ecolmodel.2008.09.006 · DOI
- 10.1126/science.1163952 · DOI · Paper page
- 10.1016/j.ecolmodel.2007.08.027 · doi:10.1016/j.ecolmodel.2007.08.027
- 10.1111/j.1365-2745.2006.01135.x · DOI
- 10.1086/605959 · DOI
- 10.1007/s10980-008-9239-2 · DOI
- 10.1016/S0022-5193(05)80681-2 · DOI · Paper page
- Huth A., 1993, Analysis of the behavior and the structure of fish schools by means of computer simulations, Coment. Theor. Biol. C, 3, 169
- 10.1093/beheco/arq149 · DOI · Paper page
- 10.1046/j.1365-2664.2000.00506.x · doi:10.1046/j.1365-2664.2000.00506.x
- 10.1103/physrevlett.69.1629 · DOI · Paper page
- 10.1071/WF9950025 · doi:10.1071/wf9950025
- 10.1007/s10021-001-0077-1 · DOI · Paper page
- 10.1016/j.ecolmodel.2008.12.026 · DOI
- Zinck R. D., Understanding shifts in wildfire regimes as emergent threshold phenomena, Am. Nat.
- 10.1038/20676 · DOI · Paper page
- 10.2307/1358 · DOI · Paper page
- Heine B.-O., 2005, Stylised facts and the contribution of simulation to the economic analysis of budgeting, J. Artif. Soc. Soc. Simul., 8
- Suter G. W. I., 1981, Ecosystem theory and NEPA assessment, Bull. Ecol. Soc. Am., 62, 186, 10.2307/20166285 · doi:10.2307/20166285
- 10.1890/1540-9295(2007)5[145:fkgipa]2.0.co;2 · DOI · Paper page
Cited by
Grimm, V., Railsback, S. F., Vincenot, C. E., Berger, U., Gallagher, C., DeAngelis, D. L., Edmonds, B., Ge, J., Giske, J., Groeneveld, J., et al. (2020) · Journal of Artificial Societies and Social Simulation · doi:10.18564/jasss.4259 · Cited by 892
Self-citationThe ecological forecast horizon, and examples of its uses and determinants
Petchey, O. L., Pontarp, M., Massie, T. M., Kéfi, S., Ozgul, A., Weilenmann, M., Palamara, G. M., Altermatt, F., Matthews, B., Levine, J. M., et al. (2015) · Ecology Letters · doi:10.1111/ele.12443 · Cited by 348
Augusiak, J., Van den Brink, P. J., & Grimm, V. (2014) · Ecological Modelling · doi:10.1016/j.ecolmodel.2013.11.009 · Cited by 296
Self-citationAnimal‐mediated seed dispersal: A review of study methods
Beckman, N. G., Kuprewicz, E. K., Borah, B., Bullock, J. M., Gallinat, A. S., González‐Varo, J. P., Jain, A., Lim, J. Y., Motta, C. I., Nevo, O., et al. (2026) · Applications in Plant Sciences · doi:10.1002/aps3.70043 · Cited by 3
Metadata
- Authors
- Grimm, V., & Railsback, S. F.
- Venue
- Philosophical Transactions of the Royal Society B: Biological Sciences
- Publisher
- The Royal Society
- Published
- 2012-01-19
- Volume
- 367
- Issue
- 1586
- Pages
- 298-310
- ISSN
- 0962-8436 (ISSN-L)
- 1471-2970
- OpenAlex
- W2145139936
- Cited by
- 426
- References
- 1
- FWCI
- 21.17
- Type
- journal article
- Language
- en
- Open access
- bronze
- Licence
- royalsociety.org/journals/ethics-policies/data-sharing-mining/ (tdm)
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Pattern-oriented modelling: a ‘multi-scope’ for predictive systems ecology. https://app.cochat.ai/papers/10.1098/rstb.2011.0180
- The paper
- Grimm, V., & Railsback, S. F. (2012). Pattern-oriented modelling: a ‘multi-scope’ for predictive systems ecology. Philosophical Transactions of the Royal Society B: Biological Sciences. https://doi.org/10.1098/rstb.2011.0180
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
